Between-Ride Routing for Private Transportation Services
Name
1810.10513.pdf
Description
Submitted version
Size
1.5 MB
Format
Adobe PDF
Checksum (MD5)
90ff16c1b3f93d42d0b70f860e849958
Author(s)
Schneider, Ian Michael
Kuan, Jun Jie Joseph
Roozbehani, Mardavij
Dahleh, Munther A
Date Issued
August 2019
Journal
2019 American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Schneider, Ian et al. "Between-Ride Routing for Private Transportation Services." 2019 American Control Conference, July 2019, Philadelphia, Pennsylvania, Institute of Electrical and Electronics Engineers, August 2019. © 2019 American Automatic Control Council
Version
Original manuscript
Abstract
Spurred by the growth of transportation network companies and increasing data capabilities, vehicle routing and ride-matching algorithms can improve the efficiency of private transportation services. However, existing routing solutions do not address where drivers should travel after dropping off a passenger and before receiving the next passenger ride request, i.e., during the between-ride period. We address this problem by developing an efficient algorithm to find the optimal policy for drivers between rides in order to maximize driver profits. We model the road network as a graph, and we show that the between-ride routing problem is equivalent to a stochastic shortest path problem, an infinite dynamic program with no discounting. We prove under reasonable assumptions that an optimal routing policy exists that avoids cycles; policies of this type can be efficiently found. We present an iterative approach to find an optimal routing policy. Our approach can account for various factors, including the frequency of passenger ride requests at different locations, traffic conditions, and surge pricing. We demonstrate the effectiveness of the approach by implementing it on road network data from Boston and New York City.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.23919/ACC.2019.8815012
